应用极化水分子模型研究单分子层受限水的介电性质

受限条件下水的介电性质因测量极具挑战,其在诸多电化学过程与反应输运过程中如何扮演关键角色从未被定量地澄清.本工作利用平衡态分子动力学模拟和受限体系介电性质计算方法,系统性地探索了0.65 nm限域尺寸、5×10⁸ Pa限域压强、不同温度条件下单分子受限冰和受限水的介电性质.详细比较了恒定偶极矩SPC/E水分子模型和可极化的SWM4-NDP水分子模型在描述受限冰、水结构与介电性质上的优劣势,包括统计分析SWM4-NDP模型模拟的单分子层受限水和受限冰的瞬时分子偶极矩概率密度分布,计算每个模拟体系的静态结构因子、静态偶极空间关联函数、静态介电常数、体系偶极时间关联函数和德拜弛豫时间.首次发现了极化水分子模型描述的低维度受限水和受限冰的奇异分子极性变化,并观察到两种模型描述静态结构性质的效果相当, SWM4-NDP模型对于静态介电常数描述的优势会因受限条件的增强而被大幅削减.但在受限水介电极化弛豫动力学性质描述上SWM4-NDP模型明显优于SPC/E模型.我们推断SWM4-NDP模型在探索受限水结构相变动力学以及受限体系离子输运和溶剂化动力学等过程的模拟研究中是比SPC...     

非晶态固体的结构可以决定性能吗?

晶态固体的力学性能与塑性变形主要由结构缺陷,比如位错的运动决定.而在非晶态固体中结构如何决定性能,仍然是固体力学、材料学和凝聚态物理学共同关心但尚未解决的核心问题之一.传统材料学研究的经典范式为"结构决定性能".遵循这一信条,已经有大量的实验表征与理论、模拟研究,尝试将非晶态固体的某种结构特征与性能建立一一对应关系.但是,科学界对于非晶固体结构-性能关系成立与否,以及背后隐藏的规律知之甚少.本文针对非晶态固体的变形机制以及其微结构特征,基于分子动力学模拟,定量评估短程简单结构与中长程复杂结构在决定非晶态固体动力学性能方面的效用.通过海量抽样每种具体玻璃结构的激活能(标识激发难易程度),尝试将结构参数与激活能建立定量关系,从而揭示出非晶态固体结构-性能关系的隐藏主控因素为结构的空间关联,受限比几何结构本身更关键.只有某种结构在空间上呈现亚纳米级的空间关联长度,这种完备结构才有可能有效地决定非晶态固体的力学性能,而短程简单结构则无效.进一步,给出了评价非晶态固体结构预测性能有效性的普适定量方法,为建立广义无序物质的结构-性能关系提供了筛选准则.     

Morris-Lecar系统中通道噪声诱导的自发性动作电位研究

在生物物理学中,越来越多的现象是由于分段确定性的动力系统与连续时间马氏过程之间的耦合作用而产生的.因为这种耦合性,相关的数学模型更适合取为随机混合系统而不是扩散过程(基于It?o随机微分方程).本文从理论上和数值上研究了在弱噪声条件下无鞍点状态的随机混合Morris-Lecar系统中,由通道噪声诱导的自发性放电现象.一个动作电位的初始阶段可视为噪声诱导的逃逸事件,其最优路径和拟势可由辅助Hamilton系统给出.由于系统不存在鞍点,因此可选择虚拟分界线(ghost separatrix)为阈值,研究噪声诱导的自静息态的逃逸事件.通过计算在阈值处的拟势,便可发现其值有一个明显的最小值,其作用类似于鞍点.通过改进的Monte Carlo模拟方法,计算了历程概率分布,其结果对初始阶段和兴奋阶段的理论解均给出了验证.此外,基于前人将拟势等高线作为阈值的另一种选择,我们对两种阈值取法的优劣性进行了比较.最后,本文研究了钠离子和钾离子通道噪声的不同组合对最优路径和拟势的影响.结果表明:钾离子通道噪声在自发性放电过程中起主导作用,且两种噪声强度存在一个最优比例能使总的噪声强度达到最小.     

Phase Engineering of CoMoO4 Anode Materials toward Improved Cycle Life for Li+ Storage

Main observation and conclusion Anode materials based on conversion reactions usually possess high energy densities for lithium-ion batteries (LIBs).However,the...     

Understanding the dehydrogenation mechanism over iron nanoparticles catalysts based on density functional theory

The conversion of chemical feedstock materials into high value-added products accompanied with dehydrogenation is of great value in the chemical industry.However,the catalytic dehydrogenation reaction is inhibited by a limited number of expensive noble metal catalysts and lacks understanding of dehydrogenation mechanism.Here,we report the use of heterogeneous non-noble metal iron nanoparticles(NPs) incorporated mesoporous nitrogen-doped carbon to investigate the dehydrogenation mechanism based on experiment observation and density functional theory(DFT) method.Fe NPs catalyst displays excellent performance in the dehydrogenation of 1,2,3,4-tetrahydroquinoline(THQ)with 100% selectivity and 100% conversion for 10-12 h at room temperature.The calculated adsorption energy implies that THQ prefers to adsorb on Fe NPs as compared with absence of Fe NPs.What is more,the energy barrier of transition state is relatively low,illustrating the dehydrogenation is feasible.This work provides an atomic scale mechanism guidance for the catalytic dehydrogenation reaction and points out the direction for the design of new catalysts.     

亚微米电喷雾喷针在非变性质谱分析中的研究进展

非变性质谱技术已成为表征蛋白质结构的重要工具之一.与传统的电喷雾喷针(Electrospray emitter,ESI emitter)相比,亚微米电喷雾喷针具有改变离子电荷态分布和降低盐离子加合等多种特性,可在生理环境下直接解析蛋白质的结构.该文综述了亚微米电喷雾喷针的特性及其在非变性质谱分析中的应用,并对其未来的发...     

Unveiling Latent Structure of Venture Capital Syndication Networks

Venture capital (VC) is a form of private equity financing provided by VC institutions to startups with high growth potential due to innovative technology or novel business models but also high risks. To against uncertainties and benefit from mutual complementarity and sharing resources and information, making joint-investments with other VC institutions on the same startup are pervasive, which forms an ever-growing complex syndication network. Attaining objective classifications of VC institutions and revealing the latent structure of joint-investment behaviors between them can deepen our understanding of the VC industry and boost the healthy development of the market and economy. In this work, we devise an iterative Loubar method based on the Lorenz curve to make objective classification of VC institutions automatically, which does not require setting arbitrary thresholds and the number of categories. We further reveal distinct investment behaviors across categories, where the top-ranked group enters more industries and investment stages with a better performance. Through network embedding of joint investment relations, we unveil the existence of possible territories of top-ranked VC institutions, and the hidden structure of relations between VC institutions.     

Statistical Degree Distribution Design for Using Fountain Codes to Control the Peak-To-Average Power Ratio in an OFDM System

Utilizing fountain codes to control the peak-to-average power ratio (PAPR) is a classic scheme in Orthogonal Frequency Division Multiplexing (OFDM) wireless communication systems. However, because the robust soliton distribution (RSD) produces large-degree values, the decoding performance is severely reduced. In this paper, we design statistical degree distribution (SD) under a scenario that utilizes fountain codes to control the PAPR. The probability of the PAPR produced is combined with RSD to design PRSD, which enhances the smaller degree value produced. Subsequently, a particle swarm optimization (PSO) algorithm is used to search the optimal degree value between the binary exponential distribution (BED) and PRSD distribution according to the minimum average degree principle. Simulation results demonstrate that the proposed method outperforms other relevant degree distributions in the same controlled PAPR threshold, and the average degree value and decoding efficiency are remarkably improved.     

Robustness Evaluation of the Open Source Product Community Network Considering Different Influential Nodes

With the rapid development of Internet technology, the innovative value and importance of the open source product community (OSPC) is becoming increasingly significant. Ensuring high robustness is essential to the stable development of OSPC with open characteristics. In robustness analysis, degree and betweenness are traditionally used to evaluate the importance of nodes. However, these two indexes are disabled to comprehensively evaluate the influential nodes in the community network. Furthermore, influential users have many followers. The effect of irrational following behavior on network robustness is also worth investigating. To solve these problems, we built a typical OSPC network using a complex network modeling method, analyzed its structural characteristics and proposed an improved method to identify influential nodes by integrating the network topology characteristics indexes. We then proposed a model containing a variety of relevant node loss strategies to simulate the changes in robustness of the OSPC network. The results showed that the proposed method can better distinguish the influential nodes in the network. Furthermore, the network’s robustness will be greatly damaged under the node loss strategies considering the influential node loss (i.e., structural hole node loss and opinion leader node loss), and the following effect can greatly change the network robustness. The results verified the feasibility and effectiveness of the proposed robustness analysis model and indexes.     

Design and Embedded Implementation of Secure Image Encryption Scheme Using DWT and 2D-LASM

In order to further improve the information effectiveness of digital image transmission, an image-encryption algorithm based on 2D-Logistic-adjusted-Sine map (2D-LASM) and Discrete Wavelet Transform (DWT) is proposed. First, a dynamic key with plaintext correlation is generated using Message-Digest Algorithm 5 (MD5), and 2D-LASM chaos is generated based on the key to obtain a chaotic pseudo-random sequence. Secondly, we perform DWT on the plaintext image to map the image from the time domain to the frequency domain and decompose the low-frequency (LF) coefficient and high-frequency (HF) coefficient. Then, the chaotic sequence is used to encrypt the LF coefficient with the structure of “confusion-permutation”. We perform the permutation operation on HF coefficient, and we reconstruct the image of the processed LF coefficient and HF coefficient to obtain the frequency-domain ciphertext image. Finally, the ciphertext is dynamically diffused using the chaotic sequence to obtain the final ciphertext. Theoretical analysis and simulation experiments show that the algorithm has a large key space and can effectively resist various attacks. Compared with the spatial-domain algorithms, this algorithm has great advantages in terms of computational complexity, security performance, and encryption efficiency. At the same time, it provides better concealment of the encrypted image while ensuring the encryption efficiency compared to existing frequency-domain methods. The successful implementation on the embedded device in the optical network environment verifies the experimental feasibility of this algorithm in the new network application.